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Biostatistics Training Program Courses

In addition to the core doctoral program curriculum, training program students are required to complete coursework in these areas:

  • at least 6 units in biomedical sciences
  • at least 6 units in biostatistics/epidemiology
  • at least 6 units in computational biology/bioinformatics/statistical genetics

While there are a large number of courses listed here and there is a substantial overlap between them, all possibilities are included to maximize flexibility, while taking into account the fact that not all classes will be offered each year and that new classes may develop. Trainee-students will be assisted by their advisor and the program directors in deciding which specific classes to take so that repetition is avoided.

Full course descriptions can be viewed at ExploreCourses.

Statistics PhD core courses

  • STATS 300ABC: Theory of Statistics (3 units)
  • STATS 305ABC: Applied Statistics (3 units)
  • STATS 310ABC: Theory of Probability (3 units)

Coursework in Biomedical Sciences

  • BIO 218: Genetic Analysis of Biological Processess (5 units)
  • BIOC 158: Genomics, Bioinformatics and Medicine (3 units)
  • GENE 202: Human Genetics (4 units)
  • GENE 205: Advanced Genetics Short Course (3 units)
  • GENE 210: Genomics and Personalized Medicine (3 units)
  • GENE 211: Genomics (3 units)
  • GENE 215: Frontiers in Biological Research (1 unit)
  • GENE 271: Human Molecular Genetics (4 units)

In addition, trainees can develop a specific directed reading course under the supervision of a faculty member: if approved by the program directors, this can count up to 3 units.

Three of these suggested classes are required by the Masters of Medicine degree, which the Medical School opens to all university PhD students (with competitive admission). This is an opportunity that trainees are encouraged to consider. Spectrum may contribute funds to cover the extra tuition costs associated with the second year of the MOM program.

Coursework in Biostatistics/Epidemiology

  • HRP 226: Advanced Epidemiologic and Clinical Research Methods (3-4 units)
  • STATS 315A: Modern Applied Statistics: Learning (2-3 units)
  • STATS 315B: Modern Applied Statistics: Data Mining (2-3 units)
  • STATS 338: Topics in Biostatistics (3 units)

Coursework in Computational Biology/Bioinformatics/Statistical Genetics

  • BIO 244: Fundamentals of Molecular Evolution (4 units)
  • BIO 283: Theoretical Population Genetics (3 units)
  • BIO 287: Advanced Topics in Human Population Genetics (3 units)
  • BIOC 218: Computational Molecular Biology (3 units)
  • BIOC 228: Computational Genomic Biology (3 units)
  • BIOMEDIN 214: Representations and Algorithms for Computational Molecular Biology (3-4 units)
  • BIOMEDIN 217: Translational Bioinformatics (4 units)
  • CS 262: Computational Genomics (3 units)
  • CS 273A: A Computational Tour of the Human Genome (3 units)
  • CS 278: Systems Biology (3 units)
  • CS 279: Computational Methods for Analysis and Reconstruction of Biological Networks (3 units)
  • CS 374: Algorithms in Biology (2-3 units)
  • GENE 244: Introduction to Statistical Genetics (3 units)
  • STATS 345: Computational Algorithms for Statistical Genetics (2-3 units)
  • STATS 366: Computational Biology (2-3 units)
  • STATS 367: Statistical Models in Genetics (2-3 units)